songsee

To generate a spectrogram from an audio file, you can use this Skill to create visual plots of audio frequencies over time. It processes your audio input and outputs detailed visual representations of the sound characteristics.

For signal processing analysis, you can visualize various audio features including Mel, Chroma, HPSS, and MFCC panels. These multi-panel visualizations help you analyze harmonic content and identify specific sonic events within a recording.

Yes, you can extract a specific time segment from an audio file for visualization. The Skill supports time slicing, allowing you to isolate and analyze specific segments of the audio in detail.

You do not strictly need ffmpeg to visualize audio formats, but it is optionally required for broader audio format support. The core processing requires the songsee binary to generate the spectrograms.

You should use MFCC or Mel spectrograms for audio analysis when you need to inspect specific frequency characteristics or harmonic content. These feature panels provide detailed visual representations of sound characteristics over time.

Your spectrogram visualization may fail for certain audio formats if you lack broader format support dependencies. Ensure you have optionally installed ffmpeg to handle a wider variety of audio inputs for the visualization process.